During the last 5-10 years, “Search” has become a phenomenon in the digital world among people all around the globe. In a typical search situation, a short search query is used to find a large, or at least a larger, document. Typical examples are Internet search engines or search engines installed on library computers for searching articles or books stored in the library.
A traditional search scenario, as described above, is different from a typical match scenario. In a match scenario, two or more users input data into a system for the purpose of finding out whether the data matches the data input by the other user(s). That is, as opposed to a search scenario, all users inputting information into the system are interested in finding matching information. In a search scenario, only the user entering the search query, typically in form of one or several key words, is interested in the match result. From a technical point of view, a matching system differs from a search engine at least in that a matching system has to index the incoming “queries” since the queries are also potential matches for previously or subsequently received queries. In order to distinguish a “match query” from a conventional search query, the data transmitted to a matching system in a “match query” will throughout this document be referred to as an “entity”.
A matching system can be used in many different types of matching services. Examples of such services are online job finding/recruitment services, E-commerce services and dating services.
A patent application PCT/EP2008/066617 previously filed by Ericsson discloses such a matching system capable of determining if a first entity received from a client device of a first user matches with at least one of a plurality of entities indexed in an index in which each entity is associated with one or more index points.
An entity may be, e.g., a text file, an image file, an audio file or any other type of data having properties that can be “translated” to words or other sequences of symbols which can serve as index points that are characterizing of the entities associated therewith.
PCT/EP2008/066617 discloses a way to perform entity insertion and search in one single operation to increase the user-perceived quality of the matching service for which the system is used, as well as to reduce the computational capacity needed in the matching systems. It also reduces the time needed to find all potential matches in the system.
In the matching system of the prior art, an entity matches another entity means that the entities have at least one index point in common, i.e. that there is at least one index point in the index with which both entities are associated. However, current matching systems are strict on the criteria for determining whether an entity should be associated with a certain index point or not. In particular, current matching system can not associate a searching entity with entities containing synonyms of the words existed in the searching entity. In other words, current matching systems can not provide more entities which are actually related to the searching entity. For example, when a searching entity contains the expression “tidy up the room”, the entity of “home cleaning” which contains the similar meaning of “tidy up the room” can not be considered as the matched one according to current matching systems, which makes current matching systems less applicable.
In addition, the actual meaning of the word is evolving, the new meanings of existing words are created due to the information communication, especially the usage of the Internet all over the world. The matching systems should be flexible enough to reflect the dynamic change of the meanings of the words.
Thus, one problem associated with matching systems according to prior art is how to provide more entities, which have the similar meanings to the searching entity but do not contain the same words of the searching entity as the matched entities, to increase the user-perceived quality of the matching service for which the system is used. Another problem is how to dynamically update the matching systems to reflect the evolved meanings of the words.